Kaiser Fung provides training and advisory services in business analytics and data visualization. He held leadership roles in building and managing data teams at Vimeo, Sirius XM Radio, [X+1], and American Express. He is the creator of the acclaimed Junk Charts blog, which pioneered the genre of critically examining graphics in the media; and author of Numbers Rule Your World and Numbersense, both published by McGraw-Hill. He has an MBA from Harvard Business School, and is an adjunct professor at New York University. His work has appeared in Harvard Business Review, American Scientist, Significance, Financial Times, Wired, FiveThirtyEight, and CNN.

Anmol Rajpurohit: Q6. Your book "Numbers Rule Your World" gives a strong impression that Statistics is for everyone and not just for Data Scientists. What are the key reasons that every individual needs to develop a basic understanding of statistics in today's world?

Kaiser Fung: One consequence of the Big Data era is that many more people have access to much more data, and generate a vast amount of analyses. A lot of coverage of Big Data focuses on the production of data and analyses but I’m very interested in their consumption. With so many analyses, there is more confusion, less consensus, and less clarity. The average citizen needs to develop numbersense to figure out who and what to believe.

AR: Q7. What inspired you to write your latest book "NumberSense"? How does it relate to your first book "Numbers Rule Your World"?

KF: I just covered the reason for writing Numbersense above. Numbersense concerns a series of analytical claims widely reported in the media in the last few years, and I describe how to probe these claims to decide whether they can be trusted. Numbersense is not something you pick up in a classroom; you learn by checking out how other people do it. Numbers Rule Your World, by contrast, is less topical and more comprehensive. It’s the book I’d use in a first course of statistics if I created the curriculum. It covers five fundamental concepts of statistics, each illustrated through two real applications, and without any math. Too frequently, I come across students who took Statistics 101, can compute all the formulas but have no idea what they are doing or why.

AR: Q8. You believe that statistics can be taught as liberal arts (in other words, it doesn't have to be taught as mathematics). What advantages do you see in teaching statistics as liberal arts?

KF: The greatest advantage of teaching introductory statistics as liberal arts is expanding its reach. One of the key insights I learned in business school is the existence of multiple modes of persuasion. Many students hate their statistics course, and I believe the reason is that the course is designed by, and thus for, logical thinkers.

The beauty of teaching statistics as liberal arts is that it emphasizes the subjective nature of data analysis. In real-world analytics, there is never a single “correct” answer. Mathematics instruction, however, drives students toward the solutions at the back of the book.

AR: Q9. Recently, we have seen a lot of Data Science related courses introduced by universities across the world. How do you assess the current academic landscape for Data Science? What are the critical components of an effective academic offering for Data Science?

KF: I’m excited to see so many schools offering training in Data Science and Analytics. I’d advise that they balance the curriculum with courses focused on developing soft skills, such as presentations and managing relationships.

AR: Q10. I admire your intellectual criticism of unthoughtful visualization involved in recent news stories. How and when did you get the motivation to start your blog "Junk Charts"?

KF: Junk Charts started almost 10 years ago when I was searching for excuses to pursue my love of writing. Blogging turned out to be perfect, especially after the readership emerged. It feels like climbing on the treadmill, as readers now expect regular updates.

AR: Q11. What is the best advice you have got in your career?

KF: The first two minutes makes or breaks your meeting.

AR: Q12. How do you think the expectations from Data Science have evolved over time? Where do you see them headed in the future?

KF: I expect that the C-suite will demand accountability from the investment in building data and analytics capabilities. I expect Data Science will become more integrated with the rest of the business.

AR: Q13. What skills do you think are the most important for practitioners in the field of Data Science?

KF: My number one wish for a new hire is numbersense. Imagine the huge dataset as a dense forest. Put people in there and trace their paths through it. Who can find the most interesting things in the least amount of time? Other than numbersense, I value soft skills highly.

AR: Q14. What was the last book that you read and liked? What do you like to do when you are not working?

KF: I am reading The Circle by Dave Eggers, which I will finish. When not working or writing, I love to travel and dine out.